Loughborough University
Browse
Revision_Final_clean.pdf (1.57 MB)

Experimental study on ice intensity and type detection for wind turbine blades with multi-channel thermocouple array sensor

Download (1.57 MB)
journal contribution
posted on 2022-04-28, 12:58 authored by Erdogan Guk, Chankyu Son, Luke Rieman, Taeseong Kim

A multi-channel thermocouple array (MCTCA) sensor has been fabricated and tested for in-situ monitoring of the temperature variation under icing conditions for wind turbine blades. The obtained temperature data is analysed as a tool to predict the icing intensity (g m−2) and type (rime and glaze) with respect to the temperature gradients. The tests are performed in an environmental chamber with a water spraying system. The temperature of the chamber is set to −15 °C to ensure the sprayed water is supercooled before reaching the apparatus surface. Based on the various tests, the following conclusions can be drawn. Firstly, the MCATA can successfully predict icing events where the maximum temperature rise is monitored as 11.9 °C for 2 mm and 9.8 °C for 3 mm resin thicknesses with the same amount of accumulated ice. Secondly, this study suggests the temperature change per unit mass as an indicator of the ice intensity. Severe icing events can be expected when the indicator converges to zero. Finally, this study found that the surface temperature gradient is changed over time due to the amount of latent heat released where the two different environmental conditions, −15 °C and −5 °C, are considered. It could be used to evaluate the ice types.

Funding

Danish EUDP support scheme for project IEA Task 19, Denmark (grant no. 64019-0515)

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Cold Regions Science and Technology

Volume

189

Publisher

Elsevier BV

Version

  • AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in the journal Cold Regions Science and Technology and the definitive published version is available at https://doi.org/10.1016/j.coldregions.2021.103297

Acceptance date

2021-05-01

Publication date

2021-05-05

Copyright date

2021

ISSN

0165-232X

eISSN

1872-7441

Language

  • en

Depositor

Erdogan Guk. Deposit date: 26 April 2022

Article number

103297

Usage metrics

    Loughborough Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC